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[Singularity Hands-on] case2: Singularity で tensorflowを動かそう (--writable ビルド, shell編)

Last updated at Posted at 2018-01-21

case2では、ソースは "Local Container"を用い、実行は "shell" コマンド でコンテナーにログインしTensorflowを起動します。また、本ページの親ページはこちらにあります。

Kobito.KseEfi.png

前提条件

Singularity がインストールされていること

Hands-on1 で作成した local上のcontainer から writableなSingularityコンテナーを作成する

Singularity コンテナーの作成

command@host
CONTAINER_NAME="wcontainer.img"
SOURCE_IMAGE="container.img"
command@host
sudo singularity build --writable ${CONTAINER_NAME} ${SOURCE_IMAGE}

生成物の確認

生成物として、Singularity用のイメージがあることを確認します。

command@host
ls -l ${CONTAINER_NAME}
response@host
-rwxr-xr-x 1 root root 1668284447 Jan 21 04:23 wcontainer.img

コンテナーの ubuntu を update する

--wirtable でコンテナーを作成したので、コンテナー内のイメージをアップデートしてみます。

command@host
sudo singularity shell --writable ${CONTAINER_NAME}
command@container
apt-get update
command@container
exit

Tensorflowの実行 (shellコマンド経由)

MNISTのサンプルスクリプトのダウンロード

command@host
wget https://raw.githubusercontent.com/tensorflow/tensorflow/r1.4/tensorflow/examples/tutorials/mnist/mnist_softmax.py

shell コマンドでコンテナーにログイン

command@host
singularity shell ${CONTAINER_NAME}
response@host
Singularity: Invoking an interactive shell within container...

MNIST on tensorflow の実行

インストールされたtensorflowを用いてMNISTを実行します。

mnist_softmax.py を実行します。

command@container
python mnist_softmax.py 
response@container
Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.
Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.
Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.
Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz
FINISH MNIST 0.9185
command@container
exit
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